Communications satellites are fundamentally limited in the capacity of data that they can deliver (as measured in bits per second) by their SWAP (size, weight and power). The amount of power available on the satellite combined with the power efficiency of the electronics, antennas, and the modulation techniques determine the amount of capacity the satellite can provide. Because capacity relates to the amount of revenue a satellite can generate, a seemingly small improvement in power efficiency can result in a large improvement in revenue, and thus profitability.
Conventional methods for optimizing the power efficiency of communications satellites involve exploring tradeoffs between various aspects of the satellite, including but not limited to antenna topologies and their characteristics, such as gain and side lobe behavior, carrier-to-interference ratio (C/I), carrier-to-noise ratio (C/N), the number of antenna beams, single carrier vs. multicarrier, the frequency reuse plan, amplifier power, amplifier backoff, pre-distortion, envelope elimination and restoration, utilized bandwidth, beamforming techniques and modulation techniques.
Conventional power optimization approaches are built around conventional and generally conservative assumptions about amplifier linearity and its typical effects on the overall system performance. Systems are generally designed to minimize nonlinearities, and may use worst-case assumptions about the effects of any nonlinearities that remain. These conventional approaches impose limitations in light of the capabilities of new and emerging nonlinear solid state power amplifiers (SSPA) (e.g., digital amplifiers) and digital ASIC technologies.
It is against this background that an improved RF chain architecture has been developed.